The Histopathological Features and CT/MRI Imaging Performances in Hepatic Angiomyolipoma Patients
Hongtao Wei*,†, Hui Liu‡, Yuhan Chen*, Xiaowei Xue§, Honglei Weng||, Huiguo Ding
,
Corresponding author
* Department of Gastroenterology and Hepatology, Beijing You’an Hospital, Capital Medical University, Center for Collaborative Innovation in Critical Infectious Diseases, Beijing, China
† Department of Emergency, Beijing Friendship Hospital, Capital Medical University, Beijing, China
‡ Department of Pathology, Beijing You’an Hospital, Capital Medical University, Beijing, China
§ Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
|| Department of Medicine II, Section Molecular Hepatology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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Sustained virologic response at post-treatment week 12 among patients treated in the first 12 months of the PEI HCV treatment program (n = 84). Individual proportions are presented. Patients received: 12 weeks paritaprevir/ritonavir/ombitasvir/dasabuvir with ribavirin (n = 73) or without ribavirin (n = 7); 24 weeks paritaprevir / ritonavir / ombitasvir / dasabuvir with ribavirin (n = 4). <span class="elsevierStyleBold">^</span> One loss to follow-up; 1 unrelated death after therapy. SVR12: sustained virologic response at post-treatment week 12. Tx: treatment.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Jordan W. Francheville, Robin Rankin, Jeremy Beck, Connie Hoare, Stefanie Materniak, Greg German, Lisa Barrett, Natalie Bunimov-Wall, Daniel Smyth" "autores" => array:9 [ 0 => array:2 [ "nombre" => "Jordan W." 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Accordingly, histopathological features of hypovascular type of HAML contained more fatty tissues and less vessels (<span class="elsevierStyleBold">a, I</span>) than hypervas-cular type HAML (<span class="elsevierStyleBold">b, II</span>) and HCC(<span class="elsevierStyleBold">c, III</span>). <span class="elsevierStyleBold">a-c:</span> HE staining, x100; I~III: CD34 IHC staining, x100.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="s0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0040">Introduction</span><p id="p0010" class="elsevierStylePara elsevierViewall">Hepatic angiomyolipoma (HAML) is one of the rare hepatic benign tumors and occurs in females more frequently, which is characterized by the composition of lipomatous, myomatous and angiomatous tissues.<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">1</span></a> Most of HAML patients are asymptomatic when they are diagnosed. Clinically, HAML and primary hepatocellular carcinoma (HCC) are often indistinguishable. According to ACG clinical guideline,<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">2</span></a> focal liver lesions in patients with liver cirrhosis should be considered a possibility of HCC. However, according to this criterion it was very difficult to distinguish HCC from liver benign tumors, particularly in those patients without liver cirrhosis.</p><p id="p0015" class="elsevierStylePara elsevierViewall">The dynamic enhanced computed tomography (CT) and magnetic resonance imaging (MRI) are very useful imaging techniques in differentiating benign lesions from malignant tumors.<a class="elsevierStyleCrossRefs" href="#bib0015"><span class="elsevierStyleSup">2,3</span></a> However, the diagnostic value of CT and MRI in discriminating HAML and HCC is unde-fined.<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">4</span></a> Hence, the aim of this study was to investigate the diagnostic value of CT and MRI in differential diagnosis of HAML and HCC in patients without cirrhosis, and to correlate the histopathological features to the CT or MRI imaging performances.</p></span><span id="s0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0045">Material and Methods</span><span id="s0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0050">Patients</span><p id="p0020" class="elsevierStylePara elsevierViewall">This was a retrospective study approved by Ethics Committee of Beijing Youan Hospital affiliated with Capital Medical University. A total of 40 nodule lesions in 6 HAML and 33 HCC patients were retrospectively analyzed. All enrolled HCC patients received surgery treatments from 2009 to 2014. The age of 6 HAML patients ranged from 30 to 66 years old. Four patients were females and the others were males. HCC candidates were enrolled according to the following criterion:<ul class="elsevierStyleList" id="l0010"><li class="elsevierStyleListItem" id="u0010"><span class="elsevierStyleLabel">•</span><p id="p0025" class="elsevierStylePara elsevierViewall">HCC without cirrhosis, confirmed histologically.</p></li><li class="elsevierStyleListItem" id="u0015"><span class="elsevierStyleLabel">•</span><p id="p0030" class="elsevierStylePara elsevierViewall">Available CT or MRI records obtained 1 month prior to the surgery.</p></li><li class="elsevierStyleListItem" id="u0020"><span class="elsevierStyleLabel">•</span><p id="p0035" class="elsevierStylePara elsevierViewall">No history of interventional therapy such as radiotherapy, transcatheter arterial chemoembolization chemotherapy (TACE).</p></li></ul></p><p id="p0040" class="elsevierStylePara elsevierViewall">The ages of 33 HCC patients ranged from 29 to 72 years-old. Thirty-one patients were males and 2 patients were females. Of 33 HCC patients, 31 had chronic hepatitis B, 1 had chronic hepatitis C. The clinical data including demography, medical history, clinical manifestations, laboratory tests and tumor information were noted from their medical records (<a class="elsevierStyleCrossRef" href="#t0010">Table 1</a>).</p><elsevierMultimedia ident="t0010"></elsevierMultimedia></span><span id="s0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0055">CT scanning</span><p id="p0045" class="elsevierStylePara elsevierViewall">The enhanced CT imaging (Lightspeed 64 VCT; GE Healthcare, Little Chalfont, Buckinghamshire, United Kingdom) was conventionally performed through injecting Iopromide (Ultravist Injection) intravenously. The methods and scanning parameters were described by Li JJ, <span class="elsevierStyleItalic">et al.</span><a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">5</span></a> The scanning parameters were as follows: 120 kV; 250-300 mA; 0.5 s/rotation; thickness, 5.0 mm; intersection gap, 5.0 mm; helical pitch (beam pitch), 0.984; and matrix: 512 x 512. Iopromide (370 mg/mL, Bayer Schering Pharma AG, Germany) was administered with dose of 1.5 mL/kg at an injection rate of 3 mL/s for a three-phase enhanced scan. Arterial phase imaging was started at 25~30 seconds after the injection of contrast medium, portal phase imaging and delayed phase imaging were started at 60~70 seconds, 180~300 seconds respectively.</p></span><span id="s0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0060">MR imaging</span><p id="p0050" class="elsevierStylePara elsevierViewall">The MRI scanning System (3.0 T, 32 Channel, SI-MENS MAGNETOM Trio A Tim System, German) was used. Dynamic scanning was performed as the patient held his breath by three dimensional volume interpolated body examination (VIBE) T1 weighted imaging (TR 3 .5 ms, TE 1. 25 ms, flip angle 9°, section thickness 3-3.5 mm, intersection gap 0.6-0.7 mm, rectangular field of view 380 mm x 285 mm, matrix 320 mm x 256 mm). The scanning time was from 18 to 25 s (median 22.5 s). Contrast agents (at a dosage of 0.1 mmol/kg) were injected by bolus tracking method at a rate of 2 mL/s, immediately followed by a 15-20 mL saline flush using an injector (Sonic shot GX, Nemoto Kyorindo Co., Ltd. Tokyo, Japan). The scanning was conventionally conducted before and after administration of Gadobenate dimeglumine (Gd-BOPTA, BRACCO PHARMA, Shanghai, China). The CT/MRI imaging was analyzed by two radiologists independently.</p></span><span id="s0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0065">Histopathological analysis</span><p id="p0055" class="elsevierStylePara elsevierViewall"><ul class="elsevierStyleList" id="l0015"><li class="elsevierStyleListItem" id="u0025"><span class="elsevierStyleLabel">•</span><p id="p0060" class="elsevierStylePara elsevierViewall">HE staining. Liver tissue specimens from surgical excised and needle biopsies was fixed in 4% poly-oxymethylene and embedded in paraffin from 33 HCC and 6 HAML patients. The liver tissue samples for HE staining was cut at 4 μm sections on a rotary microtome and staining was performed using an automated HE stainer (Leica Autostainer XL, UK).</p></li><li class="elsevierStyleListItem" id="u0030"><span class="elsevierStyleLabel">•</span><p id="p0065" class="elsevierStylePara elsevierViewall">Immunohistochemistry (IHC). Expressions of GPC3, CD34, hepatocytes, HMB-45 and SMA in liver tissue samples cut at 3 μm sections was detected with IHC staining. IHC staining was performed using an automated immunostainer (Leica Bond-Max, Milton Key-nes, UK). All sections were visualized with diaminobenzidine, counterstained with hematoxylin, and mounted in DPX. The CD34, hepatocytes, HMB-45, SMA (Monoclonal No. M716529, IR624, IR052, M0851, Dako, Denmark) and GPC3 (sc-17613, Santa Cruz, USA) primary monoclonal antibodies were diluted at 1:50 for IHC. The secondary antibody was horse-radish peroxidase (HRP)-labeled antibody (Zhongshan Golden Bridge, Beijing, China). The result was evaluated by the pathologists from the pathology department of Beijing Youan Hospital. Five high visual fields were observed with no less than 1,000 cells in each visual field. Cells in which the cytoplasm contained yellow or brown particles were considered positive.</p></li></ul></p></span><span id="s0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0070">Statistical analysis</span><p id="p0070" class="elsevierStylePara elsevierViewall">All the analyses were performed using the SPSS for Windows (version16.0, IBM Corporation, ARMONK, NY USA). The data were expressed as mean ± SD. Mann-Whitney U and Fisher exact test were used to compare the distribution of continuous and categorical variables, respectively, in the two groups. P < 0.05 was considered statistically significant.</p></span></span><span id="s0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0075">Results</span><span id="s0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0080">Clinical characteristics of HAML and HCC</span><p id="p0075" class="elsevierStylePara elsevierViewall">Compared to the HCC patients, asymptomatic single nodule and normal serum AFP were more common in the HAML patients. However, high risk factors of HCC, more non-specific symptomatic nodule and higher serum AFP were more frequently found in HCC patients (<a class="elsevierStyleCrossRef" href="#t0010">Table 1</a>). Furthermore, women had high tendency to get HAML and men had high tendency to get HCC.</p></span><span id="s0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0085">CT and MRI features</span><p id="p0080" class="elsevierStylePara elsevierViewall">Of the 39 patients, 5 HAML and 27 HCC patients had the records of contrast enhanced-CT. At the same time 5 HAML and 14 HCC patients had the records of contrast enhanced-MRI. In pre contrast enhanced-MRI, only one HAML patient showed high signal both on T1-weighted and T2-weighted imaging. However, the low signal on opposed phase T1-weighted imaging and mixed low and slightly high signal on fat-suppression T2-weighted imaging were observed in this patient. The other HAML patients and all HCC patients showed the same features, including low signal on T1-weighted imaging and high signal on T2-weighted imaging. Based on the dynamic CT and MRI performances, there were two mode types. First was the hypovascular type, in which tumor region was a weak and an unremarkable enhancement in all the periods. The second was the hypervascular type, which showed enhancement in the arterial phase and washout in the portal phase or delayed phase. Of the 5 HAML patients, 1 was hypovascular type and 4 were hypervascular type. All HCC nodule lesions showed hypervascular type. There were no significant differences between HAML and HCC groups in dynamic CT and MRI enhancement modes (P > 0.05) (<a class="elsevierStyleCrossRef" href="#t0015">Table 2</a>).</p><elsevierMultimedia ident="t0015"></elsevierMultimedia></span><span id="s0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0090">Histopathological features and CT/MRI imaging performances</span><p id="p0085" class="elsevierStylePara elsevierViewall">The CT/MRI imaging characteristics were related to the pathological features (<a class="elsevierStyleCrossRef" href="#t0020">Table 3</a>). All the HAML patients were diagnosed by histopathology composited of blood vessels, smooth muscle cells and fat tissues. However, the proportion of these three components was not the same. All the 5 hypervascular HAML patients were misdiag-nosed as HCC by CT or MRI. But the other hypovascular patient was correctly diagnosed. We also found that the tumor of HAML misdiagnostic patients (hypervascular type) contained less fat tissues and more vessels than those of hypovascular type (<a class="elsevierStyleCrossRef" href="#f0010">Figure 1</a>).</p><elsevierMultimedia ident="t0020"></elsevierMultimedia><elsevierMultimedia ident="f0010"></elsevierMultimedia></span></span><span id="s0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0095">Discussion</span><p id="p0090" class="elsevierStylePara elsevierViewall">As we known, CT and MRI examination are very useful in differentiating liver benign nodules from malignant tumors. However, a series of case reports indicated that the HAML, one of the rare hepatic benign tumors, was very difficult to differentiate from HCC. It is reported that the accurate preoperative diagnosis rate of HAML was only 25%-52%1 or even lower.<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">6</span></a> Chang Z, <span class="elsevierStyleItalic">et al.</span><a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">7</span></a> reported that the diagnosis of HAML by CT and MRI was not sensitive in a retrospective multicenter analysis of 178 patients. Kim R, <span class="elsevierStyleItalic">et al</span>.<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">8</span></a> found similar enhancement patterns of HAML and HCC during the dynamic phases of MRI. Therefore, the diagnosis of HAML remains inconclusive by CT and/or MRI and mainly relies on pathological findings. Some studies have also summarized the imaging characteristics of HAML. Yang X, <span class="elsevierStyleItalic">et al.</span><a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">9</span></a> had summarized the features of ultrasonic imaging in the non-cirrhotic focal liver lesions of HAML. They observed hyper-enhancement in the arterial phase which remains hyper-enhancement or iso-enhancement in the late phase. Cai PQ, <span class="elsevierStyleItalic">et al.</span><a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">10</span></a> retrospectively analyzed the data of 18 cases of HAML and found the early draining vein, peripheral decreasing enhancement rim and the absence of tumor capsule in the hypervascular hepatic tumor of CT or MRI imaging performances.</p><p id="p0095" class="elsevierStylePara elsevierViewall">In our data, one HAML patient showed hypovascular type by CT and MRI imaging performances. In that case, it was relatively easy to differentiate HAML from liver cancer. However, studies related to hypovascular HAML were seldom reported and hypervascular HAML were focused on by researchers.<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">11</span></a> In this study, 5 of 6 (83.3%) HAML and all the 33 HCC (100%) patients showed hypervascular type by CT and/or MRI imaging performances. Further, all 5 hypervascular type HAML patients were misdiagnosed as HCC because of the similar CT and/or MRI imaging characteristics with HCC. HAML is composed of blood vessels, smooth muscle cells and a varying amount of fat histologically. Based on the line of differentiation and predominance of tissue components in his-topathology, these tumors have been classified into 4 subtypes: mixed, lipomatous (70% fat), myomatous (10% fat), and angiomatous. The most common subtype is the mixed subtype that comprises sheets of epithelioid muscle cells admixed with islands of adipocytes and abnormal vessels. The lipomatous and myomatous patterns are regarded as morphologic variations on a continuous spectrum depending on the degree of adipose and myoid differentiation. The myomatous subtype is more common in the liver than in the kidney. Angiomatous HAML contains many large thick-walled vessels and radiologically may be misinterpreted as an intrahepatic arterial aneu-rysm. Here we also confirmed that hypovascular type HAML was rich in fat tissue (> 70%) and contained less blood vessels. Moreover, hypervascular type HAML contained less fat tissue (< 10%) and was rich in blood vessels.</p><p id="p0100" class="elsevierStylePara elsevierViewall">Notably, in the diagnosis of fat-containing lesions, MRI can provide more useful information than CT. However, it was reported that 19.6% of HCC patients were with fat-containing.<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">12</span></a> Thus, it is important to use the enhanced MRI imaging or lesion biopsy to identify benign and malignant tumors.</p><p id="p0105" class="elsevierStylePara elsevierViewall">To distinguish HAML and HCC in clinical practice, we must also pay more attention to the clinical information. In this study, we found that asymptomatic single nodule and normal serum AFP were more common in the HAML patients. On the other hand, HCC risk factors, such as hepatitis B or C virus infections, more non-specific symptomatic nodule and higher serum AFP were more frequently detected in HCC patients. Also, women had high tendency to develop HAML and men had high tendency to get HCC. These clinical features may be of great value in the differential diagnosis in the current clinical practices. To summarize for hypervascular type HAML, it is very difficult to differentiate HAML from HCC using current CT or MRI imaging techniques and we must pay attention to clinical information in clinical practices.</p></span><span id="s0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0100">Abbreviations</span><p id="p0110" class="elsevierStylePara elsevierViewall"><ul class="elsevierStyleList" id="l0020"><li class="elsevierStyleListItem" id="u0035"><span class="elsevierStyleLabel">•</span><p id="p0115" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">AFP:</span> alpha fetoprotein.</p></li><li class="elsevierStyleListItem" id="u0040"><span class="elsevierStyleLabel">•</span><p id="p0120" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">AFU:</span> α-L-fucosidase.</p></li><li class="elsevierStyleListItem" id="u0045"><span class="elsevierStyleLabel">•</span><p id="p0125" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">ALT:</span> alanine aminotransferase.</p></li><li class="elsevierStyleListItem" id="u0050"><span class="elsevierStyleLabel">•</span><p id="p0130" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">CT:</span> computed tomography.</p></li><li class="elsevierStyleListItem" id="u0055"><span class="elsevierStyleLabel">•</span><p id="p0135" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">GPC3:</span> glypican 3.</p></li><li class="elsevierStyleListItem" id="u0060"><span class="elsevierStyleLabel">•</span><p id="p0140" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">HAML:</span> hepatic angiomyolipoma.</p></li><li class="elsevierStyleListItem" id="u0065"><span class="elsevierStyleLabel">•</span><p id="p0145" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">HCC:</span> hepatocellular carcinoma.</p></li><li class="elsevierStyleListItem" id="u0070"><span class="elsevierStyleLabel">•</span><p id="p0150" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">HMB-45:</span> human melanoma black-45.</p></li><li class="elsevierStyleListItem" id="u0075"><span class="elsevierStyleLabel">•</span><p id="p0155" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">MRI:</span> magnetic resonance imaging.</p></li><li class="elsevierStyleListItem" id="u0080"><span class="elsevierStyleLabel">•</span><p id="p0160" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">NS:</span> not significant.</p></li><li class="elsevierStyleListItem" id="u0085"><span class="elsevierStyleLabel">•</span><p id="p0165" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">SMA:</span> smooth muscle actin.</p></li></ul></p></span><span id="s0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0105">Conflict of Interests</span><p id="p0170" class="elsevierStylePara elsevierViewall">The authors declared no conflict of interests.</p></span><span id="s0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0110">Acknowledgements</span><p id="p0175" class="elsevierStylePara elsevierViewall">This study was supported by the Capital Science and Technology Development Fund (2014-1-2181), Beijing Municipal Administration of Hospitals’ Clinical medicine Development of special funding (ZYLX2016-10), Beijing Municipal Administration of Hospitals’ Ascent Plan (DFL20151602) and National Natural Science Foundation (81672725). The authors also acknowledge Dr. Shi Qi and Hongjun Li, Department of Radiology in Beijing Youan Hospital, for their kindly help in data collection and imaging analysis.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:10 [ 0 => array:3 [ "identificador" => "xres1197555" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abs0010" "titulo" => "Aim" ] 1 => array:2 [ "identificador" => "abs0015" "titulo" => "Material and methods" ] 2 => array:2 [ "identificador" => "abs0020" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abs0025" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1116241" "titulo" => "Keywords" ] 2 => array:2 [ "identificador" => "s0010" "titulo" => "Introduction" ] 3 => array:3 [ "identificador" => "s0015" "titulo" => "Material and Methods" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "s0020" "titulo" => "Patients" ] 1 => array:2 [ "identificador" => "s0025" "titulo" => "CT scanning" ] 2 => array:2 [ "identificador" => "s0030" "titulo" => "MR imaging" ] 3 => array:2 [ "identificador" => "s0035" "titulo" => "Histopathological analysis" ] 4 => array:2 [ "identificador" => "s0040" "titulo" => "Statistical analysis" ] ] ] 4 => array:3 [ "identificador" => "s0045" "titulo" => "Results" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "s0050" "titulo" => "Clinical characteristics of HAML and HCC" ] 1 => array:2 [ "identificador" => "s0055" "titulo" => "CT and MRI features" ] 2 => array:2 [ "identificador" => "s0060" "titulo" => "Histopathological features and CT/MRI imaging performances" ] ] ] 5 => array:2 [ "identificador" => "s0065" "titulo" => "Discussion" ] 6 => array:2 [ "identificador" => "s0070" "titulo" => "Abbreviations" ] 7 => array:2 [ "identificador" => "s0075" "titulo" => "Conflict of Interests" ] 8 => array:2 [ "identificador" => "s0080" "titulo" => "Acknowledgements" ] 9 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2016-10-17" "fechaAceptado" => "2017-01-25" "PalabrasClave" => array:1 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1116241" "palabras" => array:4 [ 0 => "Hepatic angiomyolipoma" 1 => "Human melanoma black-45" 2 => "Hepatic benign tumors" 3 => "Hepatocellular carcinoma" ] ] ] ] "tieneResumen" => true "resumen" => array:1 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abs0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0015"><span class="elsevierStyleBold">Aim</span></span><p id="sp0040" class="elsevierStyleSimplePara elsevierViewall">To evaluate the diagnostic value of dynamic contrast-enhanced computed tomography (CT) and magnetic resonance imaging (MRI) in the differential diagnosis of hepatic angiomyolipoma (HAML) and hepatocellular carcinoma (HCC) and to clarify the relationship between histopathological features and CT or MRI imaging performances in HAML.</p></span> <span id="abs0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0020"><span class="elsevierStyleBold">Material and methods</span></span><p id="sp0045" class="elsevierStyleSimplePara elsevierViewall">Six HAML and 33 non-cirrhotic HCC patients confirmed by histopathology were retrospectively analyzed. The serum biomarkers, CT and MRI examinations were conventionally performed before the confirmatory histological diagnosis. The clinical data from their medical records was also analyzed.</p></span> <span id="abs0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0025"><span class="elsevierStyleBold">Results</span></span><p id="sp0050" class="elsevierStyleSimplePara elsevierViewall">Six HAML patients were annotated as two types according to CT and MRI imaging characteristics, including hypovascular type (n = 1) and hypervascular type (n = 5). The imaging performances of the 33 HCC patients were hypervas-cular type. Moreover, all the 5 hypervascular type HAML patients were misdiagnosed as HCC by CT or MRI. We also found that the hypervascular type of HAML patients contained more vessels and less fatty tissues in histopathology than hypovascular type of HAML patients. However, the clinical features included HCC high risk factors (hepatitis B or C), non-specific symptoms, male and increased serum alpha fetoprotein (AFP) were more common in HCC patients than HAML patients (P < 0.05, respectively).</p></span> <span id="abs0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0030"><span class="elsevierStyleBold">Conclusions</span></span><p id="sp0055" class="elsevierStyleSimplePara elsevierViewall">The CT or MRI imaging performances of HAML patients containing more vessels and less fatty tissues in histopathology resemble the imaging performance of HCC patients. These clinical features may be of great help in the differential diagnosis in the current clinical practices.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abs0010" "titulo" => "Aim" ] 1 => array:2 [ "identificador" => "abs0015" "titulo" => "Material and methods" ] 2 => array:2 [ "identificador" => "abs0020" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abs0025" "titulo" => "Conclusions" ] ] ] ] "multimedia" => array:4 [ 0 => array:7 [ "identificador" => "f0010" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1545 "Ancho" => 2074 "Tamanyo" => 628113 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0010" class="elsevierStyleSimplePara elsevierViewall">The relationship of histopathological features and CT/MRI imaging performances. <span class="elsevierStyleBold">A.</span> Hypovascular type of HAML showed a weak and unremarkable enhancement (arrow) in all periods. <span class="elsevierStyleBold">B</span>, <span class="elsevierStyleBold">C.</span> Hypervascular type of HAML and HCC showed enhancement in the arterial phase (arrow) and washout in the portal phase or delayed phase. Accordingly, histopathological features of hypovascular type of HAML contained more fatty tissues and less vessels (<span class="elsevierStyleBold">a, I</span>) than hypervas-cular type HAML (<span class="elsevierStyleBold">b, II</span>) and HCC(<span class="elsevierStyleBold">c, III</span>). <span class="elsevierStyleBold">a-c:</span> HE staining, x100; I~III: CD34 IHC staining, x100.</p>" ] ] 1 => array:7 [ "identificador" => "t0010" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Parameters \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">HAML (n = 6) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">HCC (n = 33) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">P \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age (median, range) (years) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">48.5 (30-66) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">50 (29-72) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Sex (male/female) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2/4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">31/2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.00 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Chronic liver disease (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.00 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hepatitis B \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">31 (94) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hepatitis C \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">No chronic liver disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mode of discovery (%)<span class="elsevierStyleSup">a</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.02 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Abdominal pain \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9 (31) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Abdominal discomfort \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Other symptoms (fatigue, fever) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">By chance \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14 (48) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Alanine aminotransferase (> 40 U/L) (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (17) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (24) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Aspartate aminotransferase (> 40 U/L) (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (21) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total bilirubin (> 17.1 umol/L) (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (21) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Albumin(g/L) (< 35 g/L) (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (21) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">γ-glutamyl transpeptidase (> 50 U/L) (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14 (42) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hemoglobin (< 12 g/L) (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Platelet (< 100 x 109/L) (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Fetoprotein (> 20 ng/dL) (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17 (52) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.02 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Specimen type (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Biopsy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Surgery \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">33 (100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tumor location (lobe) (%)<span class="elsevierStyleSup">b</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Right lobe \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (83) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26 (76) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Left lobe \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (21) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Caudate lobe \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (17) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">More than two lobes \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tumor number (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Unique \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">31 (94) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Multiple \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tumor size (median, range) (cm)<span class="elsevierStyleSup">b</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.2 (1.5-10.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.4 (1.4-12.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2045110.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="sp0015" class="elsevierStyleSimplePara elsevierViewall">Clinical characteristics of all enrolled patients.</p>" ] ] 2 => array:7 [ "identificador" => "t0015" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:2 [ "leyenda" => "<p id="sp0025" class="elsevierStyleSimplePara elsevierViewall">NS: no significance.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Imaging \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">HAML(%) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">HCC(%) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">P \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Contrast enhanced-CT \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hypovascular type \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (20) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hypervascular type \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (80) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27 (100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Contrast enhanced-MRI \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hypovascular type \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (20) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hypervascular type \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (80) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14 (100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2045111.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="sp0020" class="elsevierStyleSimplePara elsevierViewall">Enhancement modes CT and MRI in HAML and HCC.</p>" ] ] 3 => array:7 [ "identificador" => "t0020" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:2 [ "leyenda" => "<p id="sp0035" class="elsevierStyleSimplePara elsevierViewall">NS: no significance. ND: not done. Cells in cytoplasm taking on yellow or brown particles were considered positive. ‘-’: no positive staining. ‘+’: positive staining was weak yellow. ‘++’: positive staining was yellow. ‘++’: strong positive staining was brown.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Case No. \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">1 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">2 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">3 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">4 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">5 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">6 \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CT performance type MRI performance type \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hypovascular Hypovascular \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hypervascular Hypervascular \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hypervascular Hypervascular \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hypervascular Hypervascular \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ND Hypervascular \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hypervascular ND \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">IHC \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hepatocyte \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HMB-45 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">+ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">+ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">+ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">+++ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">+ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">+ \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SMA \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">+ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">+ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ND \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ND \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">+ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">+ \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CD34 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">+ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">++ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">++ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">++ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">++ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">++ \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">GPC3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">- \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Fat (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">> 70 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><10 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2045109.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="sp0030" class="elsevierStyleSimplePara elsevierViewall">Relationship between CT/MRI imaging performances and histopathology in 6 HAML patients.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bs0010" "bibliografiaReferencia" => array:12 [ 0 => array:3 [ "identificador" => "bib0010" "etiqueta" => "1." 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| Year/Month | Html | Total | |
|---|---|---|---|
| 2024 November | 2 | 0 | 2 |
| 2024 October | 9 | 9 | 18 |
| 2024 September | 18 | 13 | 31 |
| 2024 August | 23 | 26 | 49 |
| 2024 July | 15 | 5 | 20 |
| 2024 June | 18 | 6 | 24 |
| 2024 May | 11 | 6 | 17 |
| 2024 April | 10 | 12 | 22 |
| 2024 March | 20 | 5 | 25 |
| 2024 February | 19 | 4 | 23 |
| 2024 January | 18 | 8 | 26 |
| 2023 December | 27 | 5 | 32 |
| 2023 November | 13 | 4 | 17 |
| 2023 October | 11 | 6 | 17 |
| 2023 September | 12 | 4 | 16 |
| 2023 August | 24 | 3 | 27 |
| 2023 July | 14 | 3 | 17 |
| 2023 June | 26 | 5 | 31 |
| 2023 May | 49 | 6 | 55 |
| 2023 April | 39 | 0 | 39 |
| 2023 March | 37 | 2 | 39 |
| 2023 February | 33 | 3 | 36 |
| 2023 January | 12 | 12 | 24 |
| 2022 December | 14 | 9 | 23 |
| 2022 November | 29 | 14 | 43 |
| 2022 October | 16 | 3 | 19 |
| 2022 September | 15 | 9 | 24 |
| 2022 August | 36 | 7 | 43 |
| 2022 July | 49 | 6 | 55 |
| 2022 June | 25 | 9 | 34 |
| 2022 May | 29 | 10 | 39 |
| 2022 April | 24 | 6 | 30 |
| 2022 March | 34 | 6 | 40 |
| 2022 February | 24 | 5 | 29 |
| 2022 January | 41 | 7 | 48 |
| 2021 December | 17 | 9 | 26 |
| 2021 November | 10 | 6 | 16 |
| 2021 October | 15 | 10 | 25 |
| 2021 September | 13 | 9 | 22 |
| 2021 August | 7 | 7 | 14 |
| 2021 July | 9 | 9 | 18 |
| 2021 June | 5 | 9 | 14 |
| 2021 May | 10 | 6 | 16 |
| 2021 April | 18 | 12 | 30 |
| 2021 March | 10 | 5 | 15 |
| 2021 February | 6 | 9 | 15 |
| 2021 January | 7 | 7 | 14 |
| 2020 December | 4 | 4 | 8 |
| 2020 November | 8 | 2 | 10 |
| 2020 October | 4 | 3 | 7 |
| 2020 September | 14 | 6 | 20 |
| 2020 August | 14 | 5 | 19 |
| 2020 July | 7 | 7 | 14 |
| 2020 June | 7 | 5 | 12 |
| 2020 May | 9 | 5 | 14 |
| 2020 April | 8 | 1 | 9 |
| 2020 March | 7 | 3 | 10 |
| 2020 February | 6 | 2 | 8 |
| 2020 January | 12 | 3 | 15 |
| 2019 December | 3 | 4 | 7 |
| 2019 November | 10 | 2 | 12 |
| 2019 October | 4 | 4 | 8 |
| 2019 September | 9 | 0 | 9 |
| 2019 August | 3 | 2 | 5 |
| 2019 July | 3 | 5 | 8 |
| 2019 June | 6 | 5 | 11 |
| 2019 May | 2 | 4 | 6 |
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